The authors propose a distributed parallel adaptive lasso method called PALMS to reconstruct large-scale latent networks by leveraging multi-directional signals from nodal dynamics, significantly improving computational efficiency while maintaining estimation accuracy.
While reconstructing complete network dynamics from partial observations is theoretically possible, even when network structure is known, the success of such reconstructions is highly dependent on the observation location and significantly limited by noise magnification.